Fall 2018 Courses
Proseminar in Mass Communications
Mondays, 2:30 pm - 5:30 pm / 3 Carnegie Bldg.
The course will review and discuss the major concepts, issues and approaches involved with studying media from a social science perspective.
Pedagogy in Communications
Thursdays, 6:00 pm - 9:00 pm / 3 Carnegie Bldg.
This course focuses on the unique characteristics of undergraduate education in the communications discipline. The principles and practices covered in the seminar have applications for teaching communications in a number of venues including the academic, business and government professional settings. The course involves students in collaborative learning, assessment skills, powerful pedagogies, practical workshops and substantive reviews and applications of curricular and pedagogical research in the communications discipline.
Thursdays, 2:30- 5:30 pm / 24 Carnegie Bldg.
S. Shyam Sundar
This is a gateway course on social science research, providing students a rigorous introduction to basic methodological concepts needed for conducting empirical research. Students will learn how to explicate concepts, ask research questions and test hypotheses using experiments, surveys and content analyses. They will be introduced to descriptive and inferential statistics. They will critically analyze published research, by identifying threats to validity of inferences. They will conduct a research project from start to finish, and produce original, publishable research.
Thursdays, 3:00-6:00 pm / 3 Carnegie Bldg.
This course focuses on key theories in the social-scientific study of the individual/social effects of media use. The class explores how media shape our attitudes and behaviors in different contexts, including enjoyment, health, consumer behavior, politics, stereotyping, aggression, learning, and ongoing attitudes toward media. Course readings include scholarship on traditional media such as print, television and film as well as interactive media such as social networking sites and video games. Students should have a basic familiarity with quantitative research, but the class is ideal for anyone interested in the media, regardless of whether they have prior experience with scholarship in the area. Students are welcome even if they are taking COMM
506 concurrently or have completed equivalent coursework in another department.
Wednesdays, 12:20-1:35 pm / 3 Carnegie Bldg.
Required of all first-semester COMM graduate students, this 1-credit seminar consists of a series of individual lectures by faculty, students, or outside speakers designed to introduce the field and graduate studies in COMM at Penn State.
Data Models in Communications
Thursday, 3:30-6:30 pm / 8 Carnegie Bldg.
Mary Beth Oliver
Structural equation modeling (SEM) and related procedures have become very popular techniques in most social scientific disciplines, as they allow for more rigorous and theoretically enriching examinations of our data. The purpose of this course is to provide an introduction to and foundation for SEM contextualized in terms of applied research. It will emphasize a conceptual understanding (rather than a mathematically derived focus) of the processes involved and decisions required in conducting these types of analyses. It will illustrate how researchers often report their results in scholarly publications, and provide students with numerous opportunities to practice their skills, both during the course and on their own. Topics include
introductions to path analysis, confirmatory factor analysis, and structural equation modeling.
Case Studies in Information, Communications, and Entertainment
Mondays, 11:15 am-2:15 pm / 3 Carnegie Bldg.
This course will examine up to the minute case studies in how information, communications and entertainment (“ICE”) markets are changing as a result of entrepreneurial visions, technological innovations and other factors. We will assess recent business models, regulatory initiatives, court cases, consumer protection concerns and challenges to what society needs to achieve digital literacy. Topics include convergence, retirement of legacy technologies, the Internet of Things, the effect of computer algorithms on consumers, network neutrality, new business models for content distribution and the growing surveillance society.